Coronary Artery Bypass Grafting: Factors Related to Late Events and Saphenous Graft Patency

Overview

The purpose of this study is to determine the relations between conventional and unconventional risk factors and adverse clinical events at follow-up (including coronary bypass patency) in patients undergoing surgical myocardial revascularization.

Coronary artery bypass grafting represents one of the most frequent surgical procedure performed in the United States and Europe. The clinical benefit of myocardial revascularization is related to freedom of adverse cardiovascular events and to graft patency, above all of great saphenous vein, which is nowadays the main autologous vessel used for grafting coronaries different from anterior interventricular artery. Unfortunately, phenomena leading to early and, above all, late complications and to graft occlusion are not fully clarified and it so not possible to explain interindividual and temporary variability of progressive stenosis rate only on the basis of classical atherosclerosis risk factors. The aim of our study is to prospectively study the role of conventional risk factors (preoperative risk factors and clinical features) and of unconventional risk factors (genetic polymorphisms, inflammation and coagulation markers) with saphenous late patency and postoperative patients outcome, in particular with regard to adverse clinical events (myocardial infarction, successive stenting procedures, arrhythmias etc.)and to bypass patency. Plasma venous samples will be collected the day before surgery, at discharge from the hospital, and at follow-up from patients undergoing on-pump and off-pump coronary artery bypass grafting and stored at -80°C; Patients will be followed-up periodically with visits and telephone interviews, and will be also invited to undergo multislice (64 rows) CT scan in order to assess graft patency between 12 and 24 months after surgery. Finally the relation between conventional and unconventional risk factors with adverse events at follow-up will be assessed with multivariable statistical models.

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